AI-900: Microsoft Azure AI Fundamentals Practice Exam w/labs

AI-900: Microsoft Azure AI Fundamentals Practice Exam, a comprehensive and detailed assessment tool designed to help individuals prepare for the AI-900 certification exam. This practice exam is specifically tailored to cover all the essential topics and concepts that are required to successfully pass the Microsoft Azure AI Fundamentals exam. AI-900 certification exam is a fundamental level exam that validates an individual's knowledge and understanding of artificial intelligence concepts and how they are implemented in Microsoft Azure. By taking the AI-900: Microsoft Azure AI Fundamentals Practice Exam, candidates can assess their readiness for the actual exam and identify areas where they may need to focus their study efforts. AI-900 exam covers a wide range of topics, including machine learning, cognitive services, and natural language processing. By taking the time to study and prepare for this exam, you will gain a deep understanding of how AI technologies can be applied to real-world scenarios using Microsoft Azure. This knowledge will not only help you excel in your current role but also open up new opportunities for career advancement in the rapidly growing field of artificial intelligence. One of the key benefits of the AI-900: Microsoft Azure AI Fundamentals Practice Exam is that it is designed to closely mirror the format and content of the actual exam. This means that by completing this practice exam, you will be able to familiarize yourself with the types of questions you can expect to encounter on exam day. This will help you feel more confident and prepared, ultimately increasing your chances of passing the exam on your first attempt. In addition to helping you prepare for the exam, the AI-900: Microsoft Azure AI Fundamentals Practice Exam also provides valuable feedback on your performance. After completing the exam, you will receive a detailed score report that highlights your strengths and areas for improvement. This feedback can help you identify any gaps in your knowledge and tailor your study plan accordingly, ensuring that you are fully prepared to succeed on exam day. Another advantage of the AI-900: Microsoft Azure AI Fundamentals Practice Exam is that it is accessible anytime, anywhere. This means that you can study and practice at your own pace, fitting your exam preparation around your busy schedule. Whether you prefer to study in short bursts or dedicate long hours to exam preparation, this practice exam offers the flexibility you need to succeed. Furthermore, the AI-900: Microsoft Azure AI Fundamentals Practice Exam is an affordable and cost-effective way to prepare for the official exam. Rather than investing in expensive study materials or training courses, you can simply purchase this practice exam and start preparing right away. This makes it an ideal option for individuals looking to boost their knowledge and skills in AI without breaking the bank. **AI-900 : Microsoft Azure AI Fundamentals Exam details :** - Exam Name: Microsoft Certified - Azure AI Fundamentals - Exam Code: AI-900 - Exam Price: $99 (USD) - Number of Questions: Maximum of 40-60 questions, - Type of Questions: Multiple Choice Questions (single and multiple response), drag and drops and performance-based, - Length of Test: 60 Minutes. The exam is available in English and Japanese languages. - Passing Score: 700 / 1000 - Languages : English, Japanese, Korean, and Simplified Chinese - Schedule Exam : Pearson VUE **AI-900 : Microsoft Azure AI Fundamentals Certification Exams skill questions:** **Skill Measurement Exam Topics:** - **Describe Artificial Intelligence workloads and considerations (15–20%)** - **Describe fundamental principles of machine learning on Azure (20–25%)** - **Describe features of computer vision workloads on Azure (15–20%)** - **Describe features of Natural Language Processing (NLP) workloads on Azure (15–20%)** - **Describe features of generative AI workloads on Azure (15–20%)** **Describe Artificial Intelligence workloads and considerations (15–20%)** **Identify features of common AI workloads** - Identify features of content moderation and personalization workloads - Identify computer vision workloads - Identify natural language processing workloads - Identify knowledge mining workloads - Identify document intelligence workloads - Identify features of generative AI workloads **Identify guiding principles for responsible AI** - Describe considerations for fairness in an AI solution - Describe considerations for reliability and safety in an AI solution - Describe considerations for privacy and security in an AI solution - Describe considerations for inclusiveness in an AI solution - Describe considerations for transparency in an AI solution - Describe considerations for accountability in an AI solution **Describe fundamental principles of machine learning on Azure (20–25%)** - Identify common machine learning techniques - Identify regression machine learning scenarios - Identify classification machine learning scenarios - Identify clustering machine learning scenarios - Identify features of deep learning techniques **Describe core machine learning concepts** - Identify features and labels in a dataset for machine learning - Describe how training and validation datasets are used in machine learning **Describe Azure Machine Learning capabilities** - Describe capabilities of automated machine learning - Describe data and compute services for data science and machine learning - Describe model management and deployment capabilities in Azure Machine Learning **Describe features of computer vision workloads on Azure (15–20%)** **Identify common types of computer vision solution** - Identify features of image classification solutions - Identify features of object detection solutions - Identify features of optical character recognition solutions - Identify features of facial detection and facial analysis solutions **Identify Azure tools and services for computer vision tasks** - Describe capabilities of the Azure AI Vision service - Describe capabilities of the Azure AI Face detection service **Describe features of Natural Language Processing (NLP) workloads on Azure (15–20%)** **Identify features of common NLP Workload Scenarios** - Identify features and uses for key phrase extraction - Identify features and uses for entity recognition - Identify features and uses for sentiment analysis - Identify features and uses for language modeling - Identify features and uses for speech recognition and synthesis - Identify features and uses for translation **Identify Azure tools and services for NLP workloads** - Describe capabilities of the Azure AI Language service - Describe capabilities of the Azure AI Speech service **Describe features of generative AI workloads on Azure (15–20%)** **Identify features of generative AI solutions** - Identify features of generative AI models - Identify common scenarios for generative AI - Identify responsible AI considerations for generative AI **Identify capabilities of Azure OpenAI Service** - Describe natural language generation capabilities of Azure OpenAI Service - Describe code generation capabilities of Azure OpenAI Service - Describe image generation capabilities of Azure OpenAI Service In conclusion, the AI-900: Microsoft Azure AI Fundamentals Practice Exam is a valuable resource for anyone looking to enhance their understanding of AI technologies and their application in Microsoft Azure. By taking the time to study and prepare for this exam, you will not only increase your chances of passing the official exam but also gain a deeper appreciation for the power and potential of artificial intelligence. Don't wait any longer – invest in your future today with the AI-900: Microsoft Azure AI Fundamentals Practice Exam.